Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Minimalist coherent swarming of wireless networked autonomous mobile robots
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
Interaction and intelligent behavior
Interaction and intelligent behavior
Evolving mobile robots able to display collective behaviors
Artificial Life
Distributed, Physics-Based Control of Swarms of Vehicles
Autonomous Robots
The pros and cons of flocking in the long-range “migration” of mobile robot swarms
Theoretical Computer Science
Steering self-organized robot flocks through externally guided individuals
Neural Computing and Applications
Attractor dynamics approach to formation control: theory and application
Autonomous Robots
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
A minimalist flocking algorithm for swarm robots
ECAL'09 Proceedings of the 10th European conference on Advances in artificial life: Darwin meets von Neumann - Volume Part II
Negotiation of goal direction for cooperative transport
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
GESwarm: grammatical evolution for the automatic synthesis of collective behaviors in swarm robotics
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Hi-index | 0.00 |
In flocking, a swarm of robots moves cohesively in a common direction. Traditionally, flocking is realized using two main control rules: proximal control, which controls the cohesion of the swarm using local range-and bearing information about neighboring robots; and alignment control, which allows the robots to align in a common direction and uses more elaborate sensing mechanisms to obtain the orientation of neighboring robots. So far, limited attention has been given to motion control, used to translate the output of these two control rules into robot motion. In this paper, we propose a novel motion control method: magnitude-dependent motion control (MDMC). Through simulations and real robot experiments, we show that, with MDMC, flocking in a random direction is possible without the need for alignment control and for robots having a preferred direction of travel. MDMC has the advantage to be implementable on very simple robots that lack the capability to detect the orientation of their neighbors. In addition, we introduce a small proportion of robots informed about a desired direction of travel. We compare MDMC with a motion control method used in previous robotics literature, which we call magnitude-independent motion control (MIMC), and we show that the swarms can travel longer distances in the desired direction when using MDMC instead of MIMC. Finally, we systematically study flocking under various conditions: with or without alignment control, with or without informed robots, with MDMC or with MIMC.